Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid

22 Dec 2021

Abstract excerpt

Background: The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting therapies which will improve outcomes for patients with keloids or at risk of developing keloids. Methods: In this study, we performed single-cell RNA sequencing analysis, weighted co-expression network analysis, and differential expression...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Dermatologic Treatments and Research
Share to Hair Growth and Disorders
Share to Laser Applications in Dentistry and Medicine

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 35003102
DOI: 10.3389/fimmu.2021.783907

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for KeloidPMID 35003102Read ↗

Single-cell RNA sequencing reveals distinct immunology profiles in human keloidSemantic proximity Read ↗

Identification and validation of HOXD3 and UNC5C as molecular signatures in keloid based on weighted gene co-expression network analysisSemantic proximity Read ↗

Integration of single‐cell and bulk transcriptomics reveals immune‐related signatures in keloidSemantic proximity Read ↗

Decoding the molecular landscape of keloids: new insights from single-cell transcriptomicsSemantic proximity Read ↗

A Robust Machine Learning Framework for Keloid Biomarker Discovery Beyond Differential ExpressionSemantic proximity Read ↗

Screening of keloid immune microenvironment-related genes and their effects on keloid proliferation and migrationSemantic proximity Read ↗

Combined analyses of RNA-sequence and Hi-C along with GWAS loci-A novel approach to dissect keloid disorder genetic mechanism.Semantic proximity Read ↗

The Role of CD28 and CD8+ T Cells in Keloid DevelopmentSemantic proximity Read ↗

Keloid-Specific Gene Expression Profiling for Accurate Diagnostic and Therapeutic ApplicationsSemantic proximity Read ↗

Identifying the Pattern Characteristics of Anoikis-Related Genes in KeloidSemantic proximity Read ↗

Bioinformatics analysis and verification of m6A related genes based on the construction of keloid diagnostic modelSemantic proximity Read ↗

Identification of Biomarkers and Mechanisms for Keloid Disorder based on Comprehensive Bioinformatics Analysis and Machine Learning AlgorithmsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.